总结 | ACL2022主会论文分类整理

大家好，我是对白。

ACL 2022是CCF A类会议，人工智能领域自然语言处理（Natural Language Processing，NLP）方向最权威的国际会议之一。第60届计算语言学协会计划于今年5月22日-5月27日在爱尔兰都柏林召开。

本文对ACL 2022接受列表中的的 602篇主会长文论文，按不同的研究主题进行分类整理（分类标准参考 ACL 官方投稿主题），整理过程中难免有疏漏，欢迎大家在下方评论留言，交流探讨！

论文列表已经同步更新到 GitHub，欢迎大家关注和 Star。

目录

• Adversarial attack and Robustness【对抗攻击和鲁棒性】
• Dialogue and Interactive Systems【对话与交互系统】
• Discourse and Pragmatics【语篇和语用学】
• Data Augmentation【数据增广】
• Generation【文本生成】
• Information Extraction【信息抽取】
• Information Retrieval and Text Mining【信息检索与文本挖掘】
• Interpretability and Analysis of Models for NLP【NLP模型的可解释性与分析】
• Language Model【语言模型】
• Machine Learning for NLP【NLP中的机器学习】
• Machine Translation and Multilinguality【机器翻译与多语】
• Question Answering【问答与理解】
• Resources and Evaluation【数据集与评估方法】
• Sentence-level Semantics, Textual Classification, and Other Areas【句子级语义和关系推理】
• Semantics and Syntax Parsing【语义与句法解析】
• Speech and Multimodality【语音与多模态】
• Summation【摘要】
• Knowledge Graph【知识图谱】
• *Special Track【特殊任务】

Adversarial attack and Robustness【对抗攻击和鲁棒性】

• Adversarial Authorship Attribution for Deobfuscation
• Adversarial Soft Prompt Tuning for Cross-Domain Sentiment Analysis
• Flooding-X: Improving BERT’s Resistance to Adversarial Attacks via LossRestricted Fine-Tuning
• From the Detection of Toxic Spans in Online Discussions to the Analysis of Toxic-to-Civil Transfer
• Imputing Out-of-Vocabulary Embeddings with LOVE Makes Language Models Robust with Little Cost
• ParaDetox: Detoxification with Parallel Data
• Pass off Fish Eyes for Pearls: Attacking Model Selection of Pre-trained Models
• SHIELD: Defending Textual Neural Networks against Multiple Black-Box
• Adversarial Attacks with Stochastic Multi-Expert Patcher
• Towards Robustness of Text-to-SQL Models Against Natural and Realistic Adversarial Table Perturbation
• ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection

Dialogue and Interactive Systems【对话与交互系统】

• A Model-agnostic Data Manipulation Method for Persona-based Dialogue Generation
• A Taxonomy of Empathetic Questions in Social Dialogs
• Achieving Conversational Goals with Unsupervised Post-hoc Knowledge Injection
• Achieving Reliable Human Assessment of Open-Domain Dialogue Systems
• An Interpretable Neuro-Symbolic Reasoning Framework for Task-Oriented Dialogue Generation
• Beyond Goldfish Memory: Long-Term Open-Domain Conversation
• Beyond the Granularity: Multi-Perspective Dialogue Collaborative Selection for Dialogue State Tracking
• CASPI Causal-aware Safe Policy Improvement for Task-oriented Dialogue
• ChatMatch: Evaluating Chatbots by Autonomous Chat Tournaments
• CICERO: A Dataset for Contextualized Commonsense Inference in Dialogues
• Contextual Fine-to-Coarse Distillation for Coarse-grained Response Selection in Open-Domain Conversations
• Continual Prompt Tuning for Dialog State Tracking
• DEAM: Dialogue Coherence Evaluation using AMR-based Semantic Manipulations
• DialogVED: A Pre-trained Latent Variable Encoder-Decoder Model for Dialog Response Generation
• Dynamic Schema Graph Fusion Network for Multi-Domain Dialogue State Tracking
• GlobalWoZ: Globalizing MultiWoZ to Develop Multilingual Task-Oriented Dialogue Systems
• HeterMPC: A Heterogeneous Graph Neural Network for Response Generation in Multi-Party Conversations
• Improving Multi-label Malevolence Detection in Dialogues through Multifaceted Label Correlation Enhancement
• Interactive Word Completion for Plains Cree
• Internet-Augmented Dialogue Generation
• Knowledge Enhanced Reflection Generation for Counseling Dialogues
• M3ED: Multi-modal Multi-scene Multi-label Emotional Dialogue Database
• MISC: A Mixed Strategy-Aware Model integrating COMET for Emotional Support Conversation
• Multi-Party Empathetic Dialogue Generation: A New Task for Dialog Systems
• Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System
• Multimodal Dialogue Response Generation
• Online Semantic Parsing for Latency Reduction in Task-Oriented Dialogue
• Other Roles Matter! Enhancing Role-Oriented Dialogue Summarization via Role Interactions
• ProphetChat: Enhancing Dialogue Generation with Simulation of Future Conversation
• QAConv: Question Answering on Informative Conversations
• SaFeRDialogues: Taking Feedback Gracefully after Conversational Safety Failures
• SafetyKit: First Aid for Measuring Safety in Open-domain Conversational Systems
• SalesBot: Transitioning from Chit-Chat to Task-Oriented Dialogues
• Should a Chatbot be Sarcastic? Understanding User Preferences Towards Sarcasm Generation
• Situated Dialogue Learning through Procedural Environment Generation
• Structural Characterization for Dialogue Disentanglement
• The AI Doctor Is In: A Survey of Task-Oriented Dialogue Systems for Healthcare Applications
• There Are a Thousand Hamlets in a Thousand People’s Eyes: Enhancing Knowledge-grounded Dialogue with Personal Memory
• Think Before You Speak: Explicitly Generating Implicit Commonsense Knowledge for Response Generation
• UniTranSeR: A Unified Transformer Semantic Representation Framework for Multimodal Task-Oriented Dialog System
• What does the sea say to the shore? A BERT based DST style approach for speaker to dialogue attribution in novels
• Where to Go for the Holidays: Towards Mixed-Type Dialogs for Clarification of User Goals
• Speaker Information Can Guide Models to Better Inductive Biases: A Case Study On Predicting Code-Switching

Discourse and Pragmatics【语篇和语用学】

• CoCoLM: Complex Commonsense Enhanced Language Model with Discourse Relations
• Context Matters: A Pragmatic Study of PLMs’ Negation Understanding
• Learning to Mediate Disparities Towards Pragmatic Communication
• Modeling Persuasive Discourse to Adaptively Support Students’ Argumentative Writing
• Neural reality of argument structure constructions
• Probing for Predicate Argument Structures in Pretrained Language Models
• RST Discourse Parsing with Second-Stage EDU-Level Pre-training

Data Augmentation【数据增广】

• An Investigation of the (In)effectiveness of Counterfactually Augmented Data
• CipherDAug: Ciphertext based Data Augmentation for Neural Machine Translation
• Continual Few-shot Relation Learning via Embedding Space Regularization and Data Augmentation
• Deduplicating Training Data Makes Language Models Better
• FlipDA: Effective and Robust Data Augmentation for Few-Shot Learning
• Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasets
• Keywords and Instances: A Hierarchical Contrastive Learning Framework Unifying Hybrid Granularities for Text Generation
• MELM: Data Augmentation with Masked Entity Language Modeling for LowResource NER
• PromDA: Prompt-based Data Augmentation for Low-Resource NLU Tasks
• Synthetic Question Value Estimation for Domain Adaptation of Question Answering
• Training Data is More Valuable than You Think: A Simple and Effective Method by Retrieving from Training Data

Generation【文本生成】

• A Token-level Reference-free Hallucination Detection Benchmark for Freeform Text Generation
• A Well-Composed Text is Half Done! Composition Sampling for Diverse Conditional Generation
• Accurate Online Posterior Alignments for Principled Lexically-Constrained Decoding
• Active Evaluation: Efficient NLG Evaluation with Few Pairwise Comparisons
• AraT5: Text-to-Text Transformers for Arabic Language Generation
• Continual Sequence Generation with Adaptive Compositional Modules
• Controllable Dictionary Example Generation: Generating Example Sentences for Specific Targeted Audiences
• CTRLEval: An Unsupervised Reference-Free Metric for Evaluating Controlled Text Generation
• Few-shot Controllable Style Transfer for Low-Resource Multilingual Settings
• Fine-Grained Controllable Text Generation Using Non-Residual Prompting
• Flexible Generation from Fragmentary Linguistic Input
• FrugalScore: Learning Cheaper, Lighter and Faster Evaluation Metrics for Automatic Text Generation
• Generating Scientific Definitions with Controllable Complexity
• Hierarchical Sketch Induction for Paraphrase Generation

• How Do Seq2Seq Models Perform on End-to-End Data-to-Text Generation?

• Hybrid Semantics for Goal-Directed Natural Language Generation

• Improving Compositional Generalization with Self-Training for Data-to-Text Generation
• Improving Personalized Explanation Generation through Visualization
• Inducing Positive Perspectives with Text Reframing
• latent-GLAT: Glancing at Latent Variables for Parallel Text Generation
• Lexical Knowledge Internalization for Neural Dialog Generation
• Mix and Match: Learning-free Controllable Text Generationusing Energy Language Models
• Multitasking Framework for Unsupervised Simple Definition Generation
• Neural Pipeline for Zero-Shot Data-to-Text Generation
• Non-neural Models Matter: a Re-evaluation of Neural Referring Expression Generation Systems
• ODE Transformer: An Ordinary Differential Equation-Inspired Model for Sequence Generation
• Overlap-based Vocabulary Generation Improves Cross-lingual Transfer Among Related Languages
• PLANET: Dynamic Content Planning in Autoregressive Transformers for Long-form Text Generation
• Predicate-Argument Based Bi-Encoder for Paraphrase Identification
• Principled Paraphrase Generation with Parallel Corpora
• Quality Controlled Paraphrase Generation
• Rare Tokens Degenerate All Tokens: Improving Neural Text Generation via Adaptive Gradient Gating for Rare Token Embeddings
• RoMe: A Robust Metric for Evaluating Natural Language Generation
• Semi-Supervised Formality Style Transfer with Consistency Training
• So Different Yet So Alike! Constrained Unsupervised Text Style Transfer
• Spurious Correlations in Reference-Free Evaluation of Text Generation
• Tailor: Generating and Perturbing Text with Semantic Controls
• Towards Better Characterization of Paraphrases
• Uncertainty Determines the Adequacy of the Mode and the Tractability of Decoding in Sequence-to-Sequence Models
• An Imitation Learning Curriculum for Text Editing with Non-Autoregressive Models
• Understanding Iterative Revision from Human-Written Text

Information Extraction【信息抽取】

• Alignment-Augmented Consistent Translation for Multilingual Open Information Extraction
• Automatic Error Analysis for Document-level Information Extraction
• BenchIE: A Framework for Multi-Faceted Fact-Based Open Information Extraction Evaluation
• Dynamic Global Memory for Document-level Argument Extraction
• Dynamic Prefix-Tuning for Generative Template-based Event Extraction
• FaVIQ: FAct Verification from Information-seeking Questions
• FormNet: Structural Encoding beyond Sequential Modeling in Form Document Information Extraction
• Generating Scientific Claims for Zero-Shot Scientific Fact Checking
• JointCL: A Joint Contrastive Learning Framework for Zero-Shot Stance Detection
• KNN-Contrastive Learning for Out-of-Domain Intent Classification
• Legal Judgment Prediction via Event Extraction with Constraints
• MILIE: Modular & Iterative Multilingual Open Information Extraction
• Modeling U.S. State-Level Policies by Extracting Winners and Losers from Legislative Texts
• OIE@OIA: an Adaptable and Efficient Open Information Extraction Framework
• Packed Levitated Marker for Entity and Relation Extraction
• Pre-training to Match for Unified Low-shot Relation Extraction
• Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extraction
• Retrieval-guided Counterfactual Generation for QA
• Right for the Right Reason: Evidence Extraction for Trustworthy Tabular Reasoning
• Saliency as Evidence: Event Detection with Trigger Saliency Attribution
• Text-to-Table: A New Way of Information Extraction
• Toward Interpretable Semantic Textual Similarity via Optimal Transportbased Contrastive Sentence Learning
• Transkimmer: Transformer Learns to Layer-wise Skim
• Unified Structure Generation for Universal Information Extraction

Information Retrieval and Text Mining【信息检索与文本挖掘】

• Automatic Identification and Classification of Bragging in Social Media
• Bilingual alignment transfers to multilingual alignment for unsupervised parallel text mining

• Can Unsupervised Knowledge Transfer from Social Discussions Help Argument Mining?

• ClarET: Pre-training a Correlation-Aware Context-To-Event Transformer for Event-Centric Generation and Classification

• Cross-Lingual Phrase Retrieval
• Learning to Rank Visual Stories From Human Ranking Data
• Multi-View Document Representation Learning for Open-Domain Dense Retrieval
• New Intent Discovery with Pre-training and Contrastive Learning
• Pre-training and Fine-tuning Neural Topic Model: A Simple yet Effective Approach to Incorporating External Knowledge
• RELiC: Retrieving Evidence for Literary Claims
• Retrieval-guided Counterfactual Generation for QA
• SDR: Efficient Neural Re-ranking using Succinct Document Representation
• Sentence-aware Contrastive Learning for Open-Domain Passage Retrieval
• Show Me More Details: Discovering Hierarchies of Procedures from Semistructured Web Data
• Training Data is More Valuable than You Think: A Simple and Effective Method by Retrieving from Training Data
• UCTopic: Unsupervised Contrastive Learning for Phrase Representations and Topic Mining
• Unsupervised Corpus Aware Language Model Pre-training for Dense Passage Retrieval
• Zoom Out and Observe: News Environment Perception for Fake News Detection

Interpretability and Analysis of Models for NLP【NLP模型的可解释性与分析】

• A Closer Look at How Fine-tuning Changes BERT
• A Comparative Study of Faithfulness Metrics for Model Interpretability Methods
• A Comparison of Strategies for Source-Free Domain Adaptation
• Active Evaluation: Efficient NLG Evaluation with Few Pairwise Comparisons
• Adaptive Testing and Debugging of NLP Models
• An Empirical Study of Memorization in NLP
• An Empirical Study on Explanations in Out-of-Domain Settings
• An Empirical Survey of the Effectiveness of Debiasing Techniques for Pretrained Language Models
• An Investigation of the (In)effectiveness of Counterfactually Augmented Data

• Can Explanations Be Useful for Calibrating Black Box Models?

• Can Pre-trained Language Models Interpret Similes as Smart as Human?

• Can Prompt Probe Pretrained Language Models? Understanding the Invisible Risks from a Causal View

• Can Synthetic Translations Improve Bitext Quality?

• Can Transformer be Too Compositional? Analysing Idiom Processing in Neural Machine Translation

• Causal Probing for Grammatical Number: From Encoding to Usage
• Coherence boosting: When your pretrained language model is not paying enough attention
• Context Matters: A Pragmatic Study of PLMs’ Negation Understanding
• Cross-Lingual Ability of Multilingual Masked Language Models: A Study of Language Structure
• Dataset Geography: Mapping Language Data to Language Users

• Do Transformer Models Show Similar Attention Patterns to Task-Specific Human Gaze?

• Does Recommend-Revise Produce Reliable Annotations? An Analysis on Missing Instances in DocRED

• Explanation Graph Generation via Pre-trained Language Models: An Empirical Study with Contrastive Learning
• Finding Structural Knowledge in Multimodal-BERT
• Generating Biographies on Wikipedia: The Impact of Gender Bias on the Retrieval-Based Generation of Women Biographies
• GPT-D: Inducing Dementia-related Linguistic Anomalies by Deliberate Degradation of Artificial Neural Language Models
• How can NLP Help Revitalize Endangered Languages? A Case Study and Roadmap for the Cherokee Language
• ILDAE: Instance-Level Difficulty Analysis of Evaluation Data
• IMPLI: Investigating NLI Models’ Performance on Figurative Language
• Improving Generalizability in Implicitly Abusive Language Detection with Concept Activation Vectors
• Interpretability for Language Learners Using Example-Based Grammatical Error Correction
• Interpreting Character Embeddings With Perceptual Representations: The Case of Shape, Sound, and Color
• Investigating Failures of Automatic Translation in the Case of Unambiguous Gender
• Investigating Non-local Features for Neural Constituency Parsing
• Is Attention Explanation? An Introduction to the Debate

• Life after BERT: What do Other Muppets Understand about Language?

• Low-Rank Softmax Can Have Unargmaxable Classes in Theory but Rarely in Practice

• Measuring Fairness of Text Classifiers via Prediction Sensitivity
• Memorisation versus Generalisation in Pre-trained Language Models
• Metaphors in Pre-Trained Language Models: Probing and Generalization Across Datasets and Languages
• On the Sensitivity and Stability of Model Interpretations in NLP
• Pretraining with Artificial Language: Studying Transferable Knowledge in Language Models
• Probing as Quantifying Inductive Bias
• Probing Simile Knowledge from Pre-trained Language Models
• ProtoTEx: Explaining Model Decisions with Prototype Tensors
• Reports of personal experiences and stories in argumentation: datasets and analysis
• Rewire-then-Probe: A Contrastive Recipe for Probing Biomedical Knowledge of Pre-trained Language Models
• Sense Embeddings are also Biased – Evaluating Social Biases in Static and Contextualised Sense Embeddings
• Signal in Noise: Exploring Meaning Encoded in Random Character Sequences with Character-Aware Language Models
• Systematic Inequalities in Language Technology Performance across the World’s Languages
• That Is a Suspicious Reaction!: Interpreting Logits Variation to Detect NLP Adversarial Attacks
• The Dangers of Underclaiming: Reasons for Caution When Reporting How NLP Systems Fail
• The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments
• The Paradox of the Compositionality of Natural Language: A Neural Machine Translation Case Study
• Things not Written in Text: Exploring Spatial Commonsense from Visual Signals
• Toward Interpretable Semantic Textual Similarity via Optimal Transportbased Contrastive Sentence Learning
• Transformers in the loop: Polarity in neural models of language
• Upstream Mitigation Is Not All You Need: Testing the Bias Transfer Hypothesis in Pre-Trained Language Models
• When did you become so smart, oh wise one?! Sarcasm Explanation in Multi-modal Multi-party Dialogues
• Where to Go for the Holidays: Towards Mixed-Type Dialogs for Clarification of User Goals
• Which side are you on? Insider-Outsider classification in conspiracy theoretic social media
• Word Order Does Matter and Shuffled Language Models Know It

Language Model【语言模型】

模型结构

• ABC: Attention with Bounded-memory Control
• AdapLeR: Speeding up Inference by Adaptive Length Reduction
• AlephBERT: Language Model Pre-training and Evaluation from Sub-Word to Sentence Level
• Better Language Model with Hypernym Class Prediction
• CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight Sharing
• ClarET: Pre-training a Correlation-Aware Context-To-Event Transformer for Event-Centric Generation and Classification
• ClusterFormer: Neural Clustering Attention for Efficient and Effective Transformer
• Dependency-based Mixture Language Models
• E-LANG: Energy-Based Joint Inferencing of Super and Swift Language Models
• EPT-X: An Expression-Pointer Transformer model that generates eXplanations for numbers
• Exploring and Adapting Chinese GPT to Pinyin Input Method
• Few-Shot Tabular Data Enrichment Using Fine-Tuned Transformer Architectures
• Fine- and Coarse-Granularity Hybrid Self-Attention for Efficient BERT
• FORTAP: Using Formulas for Numerical-Reasoning-Aware Table Pretraining
• Fully Hyperbolic Neural Networks
• GLM: General Language Model Pretraining with Autoregressive Blank Infilling
• infty-former: Infinite Memory Transformer
• KinyaBERT: a Morphology-aware Kinyarwanda Language Model
• Knowledge Neurons in Pretrained Transformers
• LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understanding
• Long-range Sequence Modeling with Predictable Sparse Attention
• Low-Rank Softmax Can Have Unargmaxable Classes in Theory but Rarely in Practice
• Making Transformers Solve Compositional Tasks
• Pyramid-BERT: Reducing Complexity via Successive Core-set based Token Selection
• SkipBERT: Efficient Inference with Shallow Layer Skipping
• Sparsifying Transformer Models with Trainable Representation Pooling
• StableMoE: Stable Routing Strategy for Mixture of Experts
• TableFormer: Robust Transformer Modeling for Table-Text Encoding
• Transkimmer: Transformer Learns to Layer-wise Skim

训练策略

• The Trade-offs of Domain Adaptation for Neural Language Models
• A Simple Hash-Based Early Exiting Approach For Language Understanding and Generation
• Feeding What You Need by Understanding What You Learned
• Distinguishing Non-natural from Natural Adversarial Samples for More Robust Pre-trained Language Model
• Training Data is More Valuable than You Think: A Simple and Effective Method by Retrieving from Training Data
• ELLE: Efficient Lifelong Pre-training for Emerging Data
• LinkBERT: Pretraining Language Models with Document Links
• CoCoLM: Complex Commonsense Enhanced Language Model with Discourse Relations
• Coherence boosting: When your pretrained language model is not paying enough attention
• Feeding What You Need by Understanding What You Learned
• LinkBERT: Pretraining Language Models with Document Links
• MarkupLM: Pre-training of Text and Markup Language for Visually Rich Document Understanding
• Sparse Progressive Distillation: Resolving Overfitting under Pretrain-andFinetune Paradigm
• Token Dropping for Efficient BERT Pretraining
• XLM-E: Cross-lingual Language Model Pre-training via ELECTRA

模型压缩

• Compression of Generative Pre-trained Language Models via Quantization
• BERT Learns to Teach: Knowledge Distillation with Meta Learning
• Multi-Granularity Structural Knowledge Distillation for Language Model Compression
• Structured Pruning Learns Compact and Accurate Models

微调策略

• A Closer Look at How Fine-tuning Changes BERT
• A Good Prompt Is Worth Millions of Parameters: Low-resource Promptbased Learning for Vision-Language Models
• Adversarial Soft Prompt Tuning for Cross-Domain Sentiment Analysis
• An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels

• Are Prompt-based Models Clueless?

• bert2BERT: Towards Reusable Pretrained Language Models

• CogTaskonomy: Cognitively Inspired Task Taxonomy Is Beneficial to Transfer Learning in NLP
• Composable Sparse Fine-Tuning for Cross-Lingual Transfer
• ConTinTin: Continual Learning from Task Instructions
• Cross-Task Generalization via Natural Language Crowdsourcing Instructions
• Efficient Unsupervised Sentence Compression by Fine-tuning Transformers with Reinforcement Learning
• Enhancing Cross-lingual Natural Language Inference by Prompt-learning from Cross-lingual Templates
• Fantastically Ordered Prompts and Where to Find Them: Overcoming FewShot Prompt Order Sensitivity
• Few-Shot Learning with Siamese Networks and Label Tuning
• Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification
• On Continual Model Refinement in Out-of-Distribution Data Streams
• Overcoming Catastrophic Forgetting beyond Continual Learning: Balanced Training for Neural Machine Translation
• PPT: Pre-trained Prompt Tuning for Few-shot Learning
• Prompt-Based Rule Discovery and Boosting for Interactive WeaklySupervised Learning
• Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extraction
• Prompt-free and Efficient Few-shot Learning with Language Models
• Prototypical Verbalizer for Prompt-based Few-shot Tuning
• Turning Tables: Generating Examples from Semi-structured Tables for Endowing Language Models with Reasoning Skills
• UniPELT: A Unified Framework for Parameter-Efficient Language Model Tuning

表示学习

• A Contrastive Framework for Learning Sentence Representations from Pairwise and Triple-wise Perspective in Angular Space
• Auto-Debias: Debiasing Masked Language Models with Automated Biased Prompts
• Compact Token Representations with Contextual Quantization for Efficient Document Re-ranking
• Contextual Representation Learning beyond Masked Language Modeling
• Contrastive Visual Semantic Pretraining Magnifies the Semantics of Natural Language Representations
• Cross-Lingual Contrastive Learning for Fine-Grained Entity Typing for LowResource Languages
• Cross-Modal Discrete Representation Learning
• Debiased Contrastive Learning of Unsupervised Sentence Representations
• Enhancing Chinese Pre-trained Language Model via Heterogeneous Linguistics Graph
• GL-CLeF: A Global–Local Contrastive Learning Framework for Crosslingual Spoken Language Understanding
• Improving Event Representation via Simultaneous Weakly Supervised Contrastive Learning and Clustering
• Just Rank: Rethinking Evaluation with Word and Sentence Similarities
• Language-agnostic BERT Sentence Embedding
• Learning Disentangled Representations of Negation and Uncertainty
• Learning Disentangled Textual Representations via Statistical Measures of Similarity
• Multilingual Molecular Representation Learning via Contrastive Pre-training
• Nibbling at the Hard Core of Word Sense Disambiguation
• Noisy Channel Language Model Prompting for Few-Shot Text Classification
• Rare and Zero-shot Word Sense Disambiguation using Z-Reweighting
• Sentence-level Privacy for Document Embeddings
• Softmax Bottleneck Makes Language Models Unable to Represent Multimode Word Distributions
• SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer
• Tackling Fake News Detection by Continually Improving Social Context Representations using Graph Neural Networks
• The Grammar-Learning Trajectories of Neural Language Models
• Using Context-to-Vector with Graph Retrofitting to Improve Word Embeddings

Machine Learning for NLP【NLP中的机器学习】

• A Rationale-Centric Framework for Human-in-the-loop Machine Learning
• Bias Mitigation in Machine Translation Quality Estimation
• Disentangled Sequence to Sequence Learning for Compositional Generalization
• DoCoGen: Domain Counterfactual Generation for Low Resource Domain Adaptation
• Domain Adaptation in Multilingual and Multi-Domain Monolingual Settings for Complex Word Identification
• Domain Knowledge Transferring for Pre-trained Language Model via Calibrated Activation Boundary Distillation
• Learning Functional Distributional Semantics with Visual Data
• Leveraging Relaxed Equilibrium by Lazy Transition for Sequence Modeling
• Local Languages, Third Spaces, and other High-Resource Scenarios
• Meta-learning via Language Model In-context Tuning
• MPII: Multi-Level Mutual Promotion for Inference and Interpretation
• On the Calibration of Pre-trained Language Models using Mixup Guided by Area Under the Margin and Saliency
• Overcoming a Theoretical Limitation of Self-Attention
• Rethinking Negative Sampling for Handling Missing Entity Annotations
• Rethinking Self-Supervision Objectives for Generalizable Coherence Modeling
• Robust Lottery Tickets for Pre-trained Language Models
• Sharpness-Aware Minimization Improves Language Model Generalization
• Skill Induction and Planning with Latent Language
• The Trade-offs of Domain Adaptation for Neural Language Models
• Distributionally Robust Finetuning BERT for Covariate Drift in Spoken Language Understanding
• Learning to Imagine: Integrating Counterfactual Thinking in Neural Discrete Reasoning

Machine Translation and Multilinguality【机器翻译与多语】

翻译

• Alignment-Augmented Consistent Translation for Multilingual Open Information Extraction
• Alternative Input Signals Ease Transfer in Multilingual Machine Translation
• BiTIIMT: A Bilingual Text-infilling Method for Interactive Machine Translation
• Bridging the Data Gap between Training and Inference for Unsupervised Neural Machine Translation
• Can Transformer be Too Compositional? Analysing Idiom Processing in Neural Machine Translation
• CipherDAug: Ciphertext based Data Augmentation for Neural Machine Translation
• Conditional Bilingual Mutual Information Based Adaptive Training for Neural Machine Translation
• Confidence Based Bidirectional Global Context Aware Training Framework for Neural Machine Translation
• DEEP: DEnoising Entity Pre-training for Neural Machine Translation
• DiBiMT: A Novel Benchmark for Measuring Word Sense Disambiguation Biases in Machine Translation
• Divide and Rule: Effective Pre-Training for Context-Aware Multi-Encoder Translation Models
• EAG: Extract and Generate Multi-way Aligned Corpus for Complete Multilingual Neural Machine Translation
• Efficient Cluster-Based k-Nearest-Neighbor Machine Translation
• Flow-Adapter Architecture for Unsupervised Machine Translation
• From Simultaneous to Streaming Machine Translation by Leveraging Streaming History
• Improving Word Translation via Two-Stage Contrastive Learning
• Integrating Vectorized Lexical Constraints for Neural Machine Translation
• Investigating Failures of Automatic Translation in the Case of Unambiguous Gender
• Learning Adaptive Segmentation Policy for End-to-End Simultaneous Translation
• Learning Confidence for Transformer-based Neural Machine Translation
• Learning to Generalize to More: Continuous Semantic Augmentation for Neural Machine Translation
• Learning When to Translate for Streaming Speech
• Measuring and Mitigating Name Biases in Neural Machine Translation
• Modeling Dual Read/Write Paths for Simultaneous Machine Translation
• MSP: Multi-Stage Prompting for Making Pre-trained Language Models Better Translators
• Multilingual Document-Level Translation Enables Zero-Shot Transfer From Sentences to Documents
• Multilingual Mix: Example Interpolation Improves Multilingual Neural Machine Translation
• Neural Machine Translation with Phrase-Level Universal Visual Representations
• On Vision Features in Multimodal Machine Translation
• Overcoming Catastrophic Forgetting beyond Continual Learning: Balanced Training for Neural Machine Translation
• Prediction Difference Regularization against Perturbation for Neural Machine Translation
• Redistributing Low-Frequency Words: Making the Most of Monolingual Data in Non-Autoregressive Translation
• Reducing Position Bias in Simultaneous Machine Translation with Length Aware Framework
• Scheduled Multi-task Learning for Neural Chat Translation
• The Paradox of the Compositionality of Natural Language: A Neural Machine Translation Case Study
• Towards Making the Most of Cross-Lingual Transfer for Zero-Shot Neural Machine Translation
• Understanding and Improving Sequence-to-Sequence Pretraining for Neural Machine Translation
• Unified Speech-Text Pre-training for Speech Translation and Recognition
• UniTE: Unified Translation Evaluation
• Universal Conditional Masked Language Pre-training for Neural Machine Translation

多语

• AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languages
• Cross-Lingual Ability of Multilingual Masked Language Models: A Study of Language Structure
• Domain Adaptation in Multilingual and Multi-Domain Monolingual Settings for Complex Word Identification
• Expanding Pretrained Models to Thousands More Languages via Lexiconbased Adaptation
• Match the Script, Adapt if Multilingual: Analyzing the Effect of Multilingual Pretraining on Cross-lingual Transferability
• mLUKE: The Power of Entity Representations in Multilingual Pretrained Language Models
• Multi Task Learning For Zero Shot Performance Prediction of Multilingual Models
• Multilingual Generative Language Models for Zero-Shot Cross-Lingual Event Argument Extraction
• Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment
• Multilingual Molecular Representation Learning via Contrastive Pre-training
• Multilingual unsupervised sequence segmentation transfers to extremely low-resource languages
• One Country, 700+ Languages: NLP Challenges for Underrepresented Languages and Dialects in Indonesia
• Prix-LM: Pretraining for Multilingual Knowledge Base Construction
• Probing Structured Pruning on Multilingual Pre-trained Models: Settings, Algorithms, and Efficiency

Question Answering【问答与理解】

阅读理解

• AdaLoGN: Adaptive Logic Graph Network for Reasoning-Based Machine Reading Comprehension
• Deep Inductive Logic Reasoning for Multi-Hop Reading Comprehension
• Improving Machine Reading Comprehension with Contextualized Commonsense Knowledge
• Learning Disentangled Semantic Representations for Zero-Shot CrossLingual Transfer in Multilingual Machine Reading Comprehension
• Lite Unified Modeling for Discriminative Reading Comprehension
• Modeling Temporal-Modal Entity Graph for Procedural Multimodal Machine Comprehension

• What Makes Reading Comprehension Questions Difficult?

• MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual Data

问答

• Answer-level Calibration for Free-form Multiple Choice Question Answering
• Answering Open-Domain Multi-Answer Questions via a Recall-then-Verify Framework
• CQG: A Simple and Effective Controlled Generation Framework for Multihop Question Generation
• Ditch the Gold Standard: Re-evaluating Conversational Question Answering
• Generated Knowledge Prompting for Commonsense Reasoning
• How Do We Answer Complex Questions: Discourse Structure of Long-form Answers
• Hypergraph Transformer: Weakly-Supervised Multi-hop Reasoning for Knowledge-based Visual Question Answering
• Hyperlink-induced Pre-training for Passage Retrieval in Open-domain Question Answering
• Improving Time Sensitivity for Question Answering over Temporal Knowledge Graphs
• It is AI’s Turn to Ask Humans a Question: Question-Answer Pair Generation for Children’s Story Books
• KaFSP: Knowledge-Aware Fuzzy Semantic Parsing for Conversational Question Answering over a Large-Scale Knowledge Base
• KG-FiD: Infusing Knowledge Graph in Fusion-in-Decoder for Open-Domain Question Answering
• MMCoQA: Conversational Question Answering over Text, Tables, and Images
• Modeling Multi-hop Question Answering as Single Sequence Prediction
• On the Robustness of Question Rewriting Systems to Questions of Varying Hardness
• Open Domain Question Answering with A Unified Knowledge Interface
• Program Transfer for Answering Complex Questions over Knowledge Bases
• Retrieval-guided Counterfactual Generation for QA
• RNG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering
• Sequence-to-Sequence Knowledge Graph Completion and Question Answering
• Simulating Bandit Learning from User Feedback for Extractive Question Answering
• Subgraph Retrieval Enhanced Model for Multi-hop Knowledge Base Question Answering
• Synthetic Question Value Estimation for Domain Adaptation of Question Answering
• Your Answer is Incorrect… Would you like to know why? Introducing a Bilingual Short Answer Feedback Dataset

Resources and Evaluation【数据集与评估方法】

数据集

• A Statutory Article Retrieval Dataset in French
• CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark
• Chart-to-Text: A Large-Scale Benchmark for Chart Summarization
• CICERO: A Dataset for Contextualized Commonsense Inference in Dialogues
• CLUES: A Benchmark for Learning Classifiers using Natural Language Explanations
• ConditionalQA: A Complex Reading Comprehension Dataset with Conditional Answers
• Cree Corpus: A Collection of nêhiyawêwin Resources
• Detecting Unassimilated Borrowings in Spanish: An Annotated Corpus and Approaches to Modeling
• DialFact: A Benchmark for Fact-Checking in Dialogue
• DiBiMT: A Novel Benchmark for Measuring Word Sense Disambiguation Biases in Machine Translation
• Down and Across: Introducing Crossword-Solving as a New NLP Benchmark
• e-CARE: a New Dataset for Exploring Explainable Causal Reasoning
• EntSUM: A Data Set for Entity-Centric Extractive Summarization
• ePiC: Employing Proverbs in Context as a Benchmark for Abstract Language Understanding
• FairLex: A Multilingual Benchmark for Evaluating Fairness in Legal Text Processing
• Fantastic Questions and Where to Find Them: FairytaleQA – An Authentic Dataset for Narrative Comprehension
• Few-Shot Tabular Data Enrichment Using Fine-Tuned Transformer Architectures
• French CrowS-Pairs: Extending a challenge dataset for measuring social bias in masked language models to a language other than English
• From text to talk: Harnessing conversational corpora for humane and diversity-aware language technology
• HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language Generation
• IAM: A Comprehensive and Large-Scale Dataset for Integrated Argument Mining Tasks
• Image Retrieval from Contextual Descriptions
• KQA Pro: A Dataset with Explicit Compositional Programs for Complex Question Answering over Knowledge Base
• LexGLUE: A Benchmark Dataset for Legal Language Understanding in English
• M3ED: Multi-modal Multi-scene Multi-label Emotional Dialogue Database
• MSCTD: A Multimodal Sentiment Chat Translation Dataset
• NumGLUE: A Suite of Fundamental yet Challenging Mathematical Reasoning Tasks
• QuoteR: A Benchmark of Quote Recommendation for Writing
• Reports of personal experiences and stories in argumentation: datasets and analysis
• RNSum: A Large-Scale Dataset for Automatic Release Note Generation via Commit Logs Summarization
• SciNLI: A Corpus for Natural Language Inference on Scientific Text
• SummScreen: A Dataset for Abstractive Screenplay Summarization
• SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilities
• Textomics: A Dataset for Genomics Data Summary Generation
• The Moral Integrity Corpus: A Benchmark for Ethical Dialogue Systems
• ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection
• VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena
• WatClaimCheck: A new Dataset for Claim Entailment and Inference
• Your Answer is Incorrect… Would you like to know why? Introducing a Bilingual Short Answer Feedback Dataset

评估

• Active Evaluation: Efficient NLG Evaluation with Few Pairwise Comparisons
• AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languages
• BenchIE: A Framework for Multi-Faceted Fact-Based Open Information Extraction Evaluation
• Bias Mitigation in Machine Translation Quality Estimation
• CARETS: A Consistency And Robustness Evaluative Test Suite for VQA
• ChatMatch: Evaluating Chatbots by Autonomous Chat Tournaments
• CTRLEval: An Unsupervised Reference-Free Metric for Evaluating Controlled Text Generation
• DEAM: Dialogue Coherence Evaluation using AMR-based Semantic Manipulations
• Evaluating Factuality in Text Simplification
• FIBER: Fill-in-the-Blanks as a Challenging Video Understanding Evaluation Framework
• FrugalScore: Learning Cheaper, Lighter and Faster Evaluation Metrics for Automatic Text Generation
• Generative Pretraining for Paraphrase Evaluation
• Human Evaluation and Correlation with Automatic Metrics in Consultation Note Generation
• Is GPT-3 Text Indistinguishable from Human Text? Scarecrow: A Framework for Scrutinizing Machine Text
• Just Rank: Rethinking Evaluation with Word and Sentence Similarities
• Logic Traps in Evaluating Attribution Scores
• Quantified Reproducibility Assessment of NLP Results
• ReCLIP: A Strong Zero-Shot Baseline for Referring Expression Comprehension
• RoMe: A Robust Metric for Evaluating Natural Language Generation
• SRL4E – Semantic Role Labeling for Emotions: A Unified Evaluation Framework
• TruthfulQA: Measuring How Models Mimic Human Falsehoods
• Under the Morphosyntactic Lens: A Multifaceted Evaluation of Gender Bias in Speech Translation
• UniTE: Unified Translation Evaluation

Sentence-level Semantics, Textual Classification, and Other Areas【句子级语义和文本关系推理】

• Incorporating Hierarchy into Text Encoder: a Contrastive Learning Approach for Hierarchical Text Classification
• Adversarial Soft Prompt Tuning for Cross-Domain Sentiment Analysis
• Bag-of-Words vs. Graph vs. Sequence in Text Classification: Questioning the Necessity of Text-Graphs and the Surprising Strength of a Wide MLP
• Cluster & Tune: Boost Cold Start Performance in Text Classification
• Discrete Opinion Tree Induction for Aspect-based Sentiment Analysis
• Early Stopping Based on Unlabeled Samples in Text Classification
• Effective Token Graph Modeling using a Novel Labeling Strategy for Structured Sentiment Analysis
• Enhanced Multi-Channel Graph Convolutional Network for Aspect Sentiment Triplet Extraction
• Entailment Graph Learning with Textual Entailment and Soft Transitivity
• Evaluating Extreme Hierarchical Multi-label Classification
• FaiRR: Faithful and Robust Deductive Reasoning over Natural Language
• Improving Meta-learning for Low-resource Text Classification and Generation via Memory Imitation
• Incorporating Hierarchy into Text Encoder: a Contrastive Learning Approach for Hierarchical Text Classification
• KenMeSH: Knowledge-enhanced End-to-end Biomedical Text Labelling
• Label Semantic Aware Pre-training for Few-shot Text Classification
• Learn to Adapt for Generalized Zero-Shot Text Classification
• Leveraging Task Transferability to Meta-learning for Clinical Section Classification with Limited Data
• Measuring Fairness of Text Classifiers via Prediction Sensitivity
• On the Robustness of Offensive Language Classifiers
• Toward Interpretable Semantic Textual Similarity via Optimal Transportbased Contrastive Sentence Learning
• Towards Comprehensive Patent Approval Predictions:Beyond Traditional Document Classification

Semantics and Syntax Parsing【语义与句法解析】

语义解析

• LAGr: Label Aligned Graphs for Better Systematic Generalization in Semantic Parsing
• Fully-Semantic Parsing and Generation: the BabelNet Meaning Representation
• Graph Pre-training for AMR Parsing and Generation
• LAGr: Label Aligned Graphs for Better Systematic Generalization in Semantic Parsing
• Learned Incremental Representations for Parsing
• Learning to Generate Programs for Table Fact Verification via StructureAware Semantic Parsing
• Modeling Syntactic-Semantic Dependency Correlations in Semantic Role Labeling Using Mixture Models
• On The Ingredients of an Effective Zero-shot Semantic Parser
• Semantic Composition with PSHRG for Derivation Tree Reconstruction from Graph-Based Meaning Representations
• Towards Robustness of Text-to-SQL Models Against Natural and Realistic Adversarial Table Perturbation
• Word2Box: Capturing Set-Theoretic Semantics of Words using Box Embedding

句法分析

• Investigating Non-local Features for Neural Constituency Parsing
• Bottom-Up Constituency Parsing and Nested Named Entity Recognition with Pointer Networks
• Compositional Generalization in Dependency Parsing
• Dependency Parsing as MRC-based Span-Span Prediction
• Headed-Span-Based Projective Dependency Parsing
• Investigating Non-local Features for Neural Constituency Parsing
• Meta-Learning for Fast Cross-Lingual Adaptation in Dependency Parsing
• Phrase-aware Unsupervised Constituency Parsing
• Probing for Labeled Dependency Trees
• Semi-supervised Domain Adaptation for Dependency Parsing with Dynamic Matching Network
• Substructure Distribution Projection for Zero-Shot Cross-Lingual Dependency Parsing
• TwittIrish: A Universal Dependencies Treebank of Tweets in Modern Irish
• Unsupervised Dependency Graph Network

命名实体识别

• CONTaiNER: Few-Shot Named Entity Recognition via Contrastive Learning
• De-Bias for Generative Extraction in Unified NER Task
• Distantly Supervised Named Entity Recognition via Confidence-Based Multi-Class Positive and Unlabeled Learning
• Few-Shot Class-Incremental Learning for Named Entity Recognition
• Few-shot Named Entity Recognition with Self-describing Networks
• Good Examples Make A Faster Learner: Simple Demonstration-based Learning for Low-resource NER
• MELM: Data Augmentation with Masked Entity Language Modeling for LowResource NER
• MINER: Improving Out-of-Vocabulary Named Entity Recognition from an Information Theoretic Perspective
• Nested Named Entity Recognition as Latent Lexicalized Constituency Parsing
• Nested Named Entity Recognition with Span-level Graphs
• Parallel Instance Query Network for Named Entity Recognition

指代消解

• Adapting Coreference Resolution Models through Active Learning
• Constrained Multi-Task Learning for Bridging Resolution

实体识别，对齐与消歧

• ExtEnD: Extractive Entity Disambiguation
• FiNER: Financial Numeric Entity Recognition for XBRL Tagging
• Learning from Sibling Mentions with Scalable Graph Inference in FineGrained Entity Typing
• An Effective and Efficient Entity Alignment Decoding Algorithm via Third-Order Tensor Isomorphism
• Divide and Denoise: Learning from Noisy Labels in Fine-Grained Entity Typing with Cluster-Wise Loss Correction

其它

• A Neural Network Architecture for Program Understanding Inspired by Human Behaviors
• Bridging the Generalization Gap in Text-to-SQL Parsing with Schema Expansion
• Fair and Argumentative Language Modeling for Computational Argumentation
• LexSubCon: Integrating Knowledge from Lexical Resources into Contextual Embeddings for Lexical Substitution
• Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
• Variational Graph Autoencoding as Cheap Supervision for AMR Coreference Resolution

Speech and Multimodality【语音与多模态】

多模态

• Analyzing Generalization of Vision and Language Navigation to Unseen Outdoor Areas
• CARETS: A Consistency And Robustness Evaluative Test Suite for VQA
• CLIP Models are Few-Shot Learners: Empirical Studies on VQA and Visual Entailment
• Contrastive Visual Semantic Pretraining Magnifies the Semantics of Natural Language Representations
• End-to-End Modeling via Information Tree for One-Shot Natural Language Spatial Video Grounding
• Guided Attention Multimodal Multitask Financial Forecasting with InterCompany Relationships and Global and Local News
• Image Retrieval from Contextual Descriptions
• Letters From the Past: Modeling Historical Sound Change Through Diachronic Character Embeddings
• Leveraging Visual Knowledge in Language Tasks: An Empirical Study on Intermediate Pre-training for Cross-Modal Knowledge Transfer
• Modeling Temporal-Modal Entity Graph for Procedural Multimodal Machine Comprehension
• Multi-Modal Sarcasm Detection via Cross-Modal Graph Convolutional Network
• Multimodal Dialogue Response Generation
• Multimodal fusion via cortical network inspired losses
• Multimodal Sarcasm Target Identification in Tweets
• On Vision Features in Multimodal Machine Translation
• OpenHands: Making Sign Language Recognition Accessible with Posebased Pretrained Models across Languages
• Phone-ing it in: Towards Flexible Multi-Modal Language Model Training by Phonetic Representations of Data
• Premise-based Multimodal Reasoning: Conditional Inference on Joint Textual and Visual Clues
• RoCBert: Robust Chinese Bert with Multimodal Contrastive Pretraining
• There’s a Time and Place for Reasoning Beyond the Image
• Things not Written in Text: Exploring Spatial Commonsense from Visual Signals
• Understanding Multimodal Procedural Knowledge by Sequencing Multimodal Instructional Manuals
• UniTranSeR: A Unified Transformer Semantic Representation Framework for Multimodal Task-Oriented Dialog System
• Vision-and-Language Navigation: A Survey of Tasks, Methods, and Future Directions
• Vision-Language Pre-Training for Multimodal Aspect-Based Sentiment Analysis
• Visual-Language Navigation Pretraining via Prompt-based Environmental Self-exploration
• WikiDiverse: A Multimodal Entity Linking Dataset with Diversified Contextual Topics and Entity Types

语音

• Cross-Utterance Conditioned VAE for Non-Autoregressive Text-to-Speech
• Decoding Part-of-Speech from Human EEG Signals
• Direct Speech-to-Speech Translation With Discrete Units
• Language-Agnostic Meta-Learning for Low-Resource Text-to-Speech with Articulatory Features
• Leveraging Unimodal Self-Supervised Learning for Multimodal Audio-Visual Speech Recognition
• Requirements and Motivations of Low-Resource Speech Synthesis for Language Revitalization
• Revisiting Over-Smoothness in Text to Speech
• Self-supervised Semantic-driven Phoneme Discovery for Zero-resource Speech Recognition
• SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing
• STEMM: Self-learning with Speech-text Manifold Mixup for Speech Translation
• Text-Free Prosody-Aware Generative Spoken Language Modeling
• Do self-supervised speech models develop human-like perception biases?

Summation【摘要】

• A Multi-Document Coverage Reward for RELAXed Multi-Document Summarization
• A Variational Hierarchical Model for Neural Cross-Lingual Summarization
• ASPECTNEWS: Aspect-Oriented Summarization of News Documents
• Attention Temperature Matters in Abstractive Summarization Distillation
• BRIO: Bringing Order to Abstractive Summarization
• Chart-to-Text: A Large-Scale Benchmark for Chart Summarization
• Differentiable Multi-Agent Actor-Critic for Multi-Step Radiology Report Summarization
• Discriminative Marginalized Probabilistic Neural Method for Multi-Document Summarization of Medical Literature
• DYLE: Dynamic Latent Extraction for Abstractive Long-Input Summarization
• Educational Question Generation of Children Storybooks via Question Type Distribution Learning and Event-centric Summarization
• EntSUM: A Data Set for Entity-Centric Extractive Summarization
• Graph Enhanced Contrastive Learning for Radiology Findings Summarization
• Hallucinated but Factual! Inspecting the Factuality of Hallucinations in Abstractive Summarization
• HIBRIDS: Attention with Hierarchical Biases for Structure-aware Long Document Summarization
• Learning Non-Autoregressive Models from Search for Unsupervised Sentence Summarization
• Learning the Beauty in Songs: Neural Singing Voice Beautifier
• Length Control in Abstractive Summarization by Pretraining Information Selection
• MemSum: Extractive Summarization of Long Documents Using Multi-Step Episodic Markov Decision Processes
• Neural Label Search for Zero-Shot Multi-Lingual Extractive Summarization
• Other Roles Matter! Enhancing Role-Oriented Dialogue Summarization via Role Interactions
• Predicting Intervention Approval in Clinical Trials through Multi-Document Summarization
• PRIMERA: Pyramid-based Masked Sentence Pre-training for Multidocument Summarization
• Summ^N: A Multi-Stage Summarization Framework for Long Input Dialogues and Documents
• SummaReranker: A Multi-Task Mixture-of-Experts Re-ranking Framework for Abstractive Summarization
• The patient is more dead than alive: exploring the current state of the multidocument summarisation of the biomedical literature
• Towards Abstractive Grounded Summarization of Podcast Transcripts
• Unsupervised Extractive Opinion Summarization Using Sparse Coding
• Updated Headline Generation: Creating Updated Summaries for Evolving News Stories

Knowledge Graph【知识图谱】

• CAKE: A Scalable Commonsense-Aware Framework For Multi-View Knowledge Graph Completion
• Efficient Hyper-parameter Search for Knowledge Graph Embedding
• KaFSP: Knowledge-Aware Fuzzy Semantic Parsing for Conversational Question Answering over a Large-Scale Knowledge Base
• Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment
• Prix-LM: Pretraining for Multilingual Knowledge Base Construction
• RotateQVS: Representing Temporal Information as Rotations in Quaternion Vector Space for Temporal Knowledge Graph Completion
• Sequence-to-Sequence Knowledge Graph Completion and Question Answering
• SimKGC: Simple Contrastive Knowledge Graph Completion with Pretrained Language Models
• Understanding Gender Bias in Knowledge Base Embeddings

Special Track【特殊任务】

Code Relevant

• Accelerating Code Search with Deep Hashing and Code Classification
• Impact of Evaluation Methodologies on Code Summarization
• Modeling Hierarchical Syntax Structure with Triplet Position for Source Code Summarization
• Towards Learning (Dis)-Similarity of Source Code from Program Contrasts
• UniXcoder: Unified Cross-Modal Pre-training for Code Representation
• ReACC: A Retrieval-Augmented Code Completion Framework
• Impact of Evaluation Methodologies on Code Summarization

Math Problem

• Learning to Reason Deductively: Math Word Problem Solving as Complex Relation Extraction
• Continual Pre-training of Language Models for Math Problem Understanding with Syntax-Aware Memory Network
• NumGLUE: A Suite of Fundamental yet Challenging Mathematical Reasoning Tasks

Word / Sentence Segmentation

• Weakly Supervised Word Segmentation for Computational Language Documentation
• Word Segmentation as Unsupervised Constituency Parsing
• That Slepen Al the Nyght with Open Ye! Cross-era Sequence Segmentation with Switch-memory
• TopWORDS-Seg: Simultaneous Text Segmentation and Word Discovery for Open-Domain Chinese Texts via Bayesian Inference

Others

• Automated Crossword Solving
• CaMEL: Case Marker Extraction without Labels
• Characterizing Idioms: Conventionality and Contingency
• Challenges and Strategies in Cross-Cultural NLP
• Clickbait Spoiling via Question Answering and Passage Retrieval
• Computational Historical Linguistics and Language Diversity in South Asia
• Doctor Recommendation in Online Health Forums via Expertise Learning
• Ensembling and Knowledge Distilling of Large Sequence Taggers for Grammatical Error Correction
• Entity-based Neural Local Coherence Modeling
• Ethics Sheets for AI Tasks
• HOLM: Hallucinating Objects with Language Models for Referring Expression Recognition in Partially-Observed Scenes
• Identifying Chinese Opinion Expressions with Extremely-Noisy Crowdsourcing Annotations
• Identifying Moments of Change from Longitudinal User Text
• Identifying the Human Values behind Arguments
• Improving the Generalizability of Depression Detection by Leveraging Clinical Questionnaires
• Incorporating Stock Market Signals for Twitter Stance Detection
• Inferring Rewards from Language in Context
• Large Scale Substitution-based Word Sense Induction
• Learning From Failure: Data Capture in an Australian Aboriginal Community
• Leveraging Similar Users for Personalized Language Modeling with Limited Data
• Leveraging Wikipedia article evolution for promotional tone detection
• Misinfo Reaction Frames: Reasoning about Readers’ Reactions to News Headlines
• Multilingual Detection of Personal Employment Status on Twitter
• Not always about you: Prioritizing community needs when developing endangered language technology
• Perceiving the World: Question-guided Reinforcement Learning for Text-based Games
• Reinforcement Guided Multi-Task Learning Framework for Low-Resource Stereotype Detection
• Searching for fingerspelled content in American Sign Language
• Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang
• Toward Annotator Group Bias in Crowdsourcing
• Towards Afrocentric NLP for African Languages: Where We Are and Where We Can Go
• Uncertainty Estimation of Transformer Predictions for Misclassification Detection
• VALUE: Understanding Dialect Disparity in NLU
• You might think about slightly revising the title: Identifying Hedges in Peertutoring Interactions
• A Functionalist Account of Vowel System Typology

关于我

你好，我是对白，清华计算机硕士毕业，现大厂算法工程师，拿过8家大厂算法岗SSP offer（含特殊计划），薪资40+W-80+W不等。

高中荣获全国数学和化学竞赛二等奖。

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我每周至少更新三篇原创，分享人工智能前沿算法、创业心得和人生感悟。我正在努力实现人生中的第二个小目标，上方关注后可以加我微信交流。

Original: https://blog.csdn.net/qq_33161208/article/details/124407668
Author: 程序员对白
Title: 总结 | ACL2022主会论文分类整理